Overview

Dataset statistics

Number of variables28
Number of observations119390
Missing cells129425
Missing cells (%)3.9%
Duplicate rows22
Duplicate rows (%)< 0.1%
Total size in memory24.7 MiB
Average record size in memory217.0 B

Variable types

Categorical13
Numeric14
Boolean1

Alerts

Dataset has 22 (< 0.1%) duplicate rowsDuplicates
country has a high cardinality: 177 distinct values High cardinality
year_arrival_date is highly correlated with week_number_arrival_dateHigh correlation
week_number_arrival_date is highly correlated with year_arrival_dateHigh correlation
repeated_guest is highly correlated with num_previous_staysHigh correlation
num_previous_stays is highly correlated with repeated_guestHigh correlation
year_arrival_date is highly correlated with week_number_arrival_dateHigh correlation
week_number_arrival_date is highly correlated with year_arrival_dateHigh correlation
repeated_guest is highly correlated with num_previous_staysHigh correlation
num_previous_stays is highly correlated with repeated_guestHigh correlation
type is highly correlated with id_travel_agency_booking and 2 other fieldsHigh correlation
days_between_booking_arrival is highly correlated with id_person_bookingHigh correlation
year_arrival_date is highly correlated with month_arrival_date and 1 other fieldsHigh correlation
month_arrival_date is highly correlated with year_arrival_date and 1 other fieldsHigh correlation
week_number_arrival_date is highly correlated with year_arrival_date and 2 other fieldsHigh correlation
num_weekend_nights is highly correlated with num_workweek_nights and 1 other fieldsHigh correlation
num_workweek_nights is highly correlated with num_weekend_nightsHigh correlation
num_children is highly correlated with reserved_roomHigh correlation
market_segment is highly correlated with distribution_channel and 3 other fieldsHigh correlation
distribution_channel is highly correlated with market_segmentHigh correlation
num_previous_cancellations is highly correlated with num_previous_staysHigh correlation
num_previous_stays is highly correlated with num_previous_cancellationsHigh correlation
reserved_room is highly correlated with num_children and 1 other fieldsHigh correlation
changes_between_booking_arrival is highly correlated with num_weekend_nightsHigh correlation
deposit_policy is highly correlated with market_segmentHigh correlation
id_travel_agency_booking is highly correlated with type and 1 other fieldsHigh correlation
id_person_booking is highly correlated with type and 5 other fieldsHigh correlation
customer_type is highly correlated with market_segmentHigh correlation
avg_price is highly correlated with type and 2 other fieldsHigh correlation
id_travel_agency_booking has 16340 (13.7%) missing values Missing
id_person_booking has 112593 (94.3%) missing values Missing
num_previous_cancellations is highly skewed (γ1 = 24.45804872) Skewed
num_previous_stays is highly skewed (γ1 = 23.53979995) Skewed
days_between_booking_arrival has 6345 (5.3%) zeros Zeros
num_weekend_nights has 51998 (43.6%) zeros Zeros
num_workweek_nights has 7645 (6.4%) zeros Zeros
market_segment has 12606 (10.6%) zeros Zeros
num_previous_cancellations has 112906 (94.6%) zeros Zeros
num_previous_stays has 115770 (97.0%) zeros Zeros
changes_between_booking_arrival has 101314 (84.9%) zeros Zeros
avg_price has 1960 (1.6%) zeros Zeros
total_of_special_requests has 70318 (58.9%) zeros Zeros

Reproduction

Analysis started2022-03-16 23:54:15.047797
Analysis finished2022-03-16 23:55:42.622456
Duration1 minute and 27.57 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

type
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
Hotel
79330 
Fancy Hotel
40060 

Length

Max length11
Median length5
Mean length7.013233939
Min length5

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFancy Hotel
2nd rowFancy Hotel
3rd rowFancy Hotel
4th rowFancy Hotel
5th rowFancy Hotel

Common Values

ValueCountFrequency (%)
Hotel79330
66.4%
Fancy Hotel40060
33.6%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
hotel119390
74.9%
fancy40060
 
25.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

cancellation
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
0
75166 
1
44224 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
075166
63.0%
144224
37.0%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
075166
63.0%
144224
37.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

days_between_booking_arrival
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct479
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.0114164
Minimum0
Maximum737
Zeros6345
Zeros (%)5.3%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile0
Q118
median69
Q3160
95-th percentile320
Maximum737
Range737
Interquartile range (IQR)142

Descriptive statistics

Standard deviation106.863097
Coefficient of variation (CV)1.027416997
Kurtosis1.696448849
Mean104.0114164
Median Absolute Deviation (MAD)60
Skewness1.346549873
Sum12417923
Variance11419.72151
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
06345
 
5.3%
13460
 
2.9%
22069
 
1.7%
31816
 
1.5%
41715
 
1.4%
51565
 
1.3%
61445
 
1.2%
71331
 
1.1%
81138
 
1.0%
121079
 
0.9%
Other values (469)97427
81.6%
ValueCountFrequency (%)
06345
5.3%
13460
2.9%
22069
 
1.7%
31816
 
1.5%
41715
 
1.4%
51565
 
1.3%
61445
 
1.2%
71331
 
1.1%
81138
 
1.0%
9992
 
0.8%
ValueCountFrequency (%)
7371
 
< 0.1%
7091
 
< 0.1%
62917
< 0.1%
62630
< 0.1%
62217
< 0.1%
61517
< 0.1%
60817
< 0.1%
60530
< 0.1%
60117
< 0.1%
59417
< 0.1%

year_arrival_date
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
2016
56707 
2017
40687 
2015
21996 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015
2nd row2015
3rd row2015
4th row2015
5th row2015

Common Values

ValueCountFrequency (%)
201656707
47.5%
201740687
34.1%
201521996
 
18.4%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
201656707
47.5%
201740687
34.1%
201521996
 
18.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

month_arrival_date
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
August
13877 
July
12661 
May
11791 
October
11160 
April
11089 
Other values (7)
58812 

Length

Max length9
Median length6
Mean length5.903182846
Min length3

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJuly
2nd rowJuly
3rd rowJuly
4th rowJuly
5th rowJuly

Common Values

ValueCountFrequency (%)
August13877
11.6%
July12661
10.6%
May11791
9.9%
October11160
9.3%
April11089
9.3%
June10939
9.2%
September10508
8.8%
March9794
8.2%
February8068
6.8%
November6794
5.7%
Other values (2)12709
10.6%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
august13877
11.6%
july12661
10.6%
may11791
9.9%
october11160
9.3%
april11089
9.3%
june10939
9.2%
september10508
8.8%
march9794
8.2%
february8068
6.8%
november6794
5.7%
Other values (2)12709
10.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

week_number_arrival_date
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct53
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.16517296
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum1
5-th percentile5
Q116
median28
Q338
95-th percentile49
Maximum53
Range52
Interquartile range (IQR)22

Descriptive statistics

Standard deviation13.60513836
Coefficient of variation (CV)0.500830176
Kurtosis-0.9860771763
Mean27.16517296
Median Absolute Deviation (MAD)11
Skewness-0.01001432604
Sum3243250
Variance185.0997897
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
333580
 
3.0%
303087
 
2.6%
323045
 
2.6%
343040
 
2.5%
182926
 
2.5%
212854
 
2.4%
282853
 
2.4%
172805
 
2.3%
202785
 
2.3%
292763
 
2.3%
Other values (43)89652
75.1%
ValueCountFrequency (%)
11047
0.9%
21218
1.0%
31319
1.1%
41487
1.2%
51387
1.2%
61508
1.3%
72109
1.8%
82216
1.9%
92117
1.8%
102149
1.8%
ValueCountFrequency (%)
531816
1.5%
521195
1.0%
51933
0.8%
501505
1.3%
491782
1.5%
481504
1.3%
471685
1.4%
461574
1.3%
451941
1.6%
442272
1.9%

day_of_month_arrival_date
Real number (ℝ≥0)

Distinct31
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.79824106
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile30
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.780829471
Coefficient of variation (CV)0.5558105765
Kurtosis-1.187168319
Mean15.79824106
Median Absolute Deviation (MAD)8
Skewness-0.002000453979
Sum1886152
Variance77.10296619
MonotonicityNot monotonic
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
174406
 
3.7%
54317
 
3.6%
154196
 
3.5%
254160
 
3.5%
264147
 
3.5%
94096
 
3.4%
124087
 
3.4%
164078
 
3.4%
24055
 
3.4%
194052
 
3.4%
Other values (21)77796
65.2%
ValueCountFrequency (%)
13626
3.0%
24055
3.4%
33855
3.2%
43763
3.2%
54317
3.6%
63833
3.2%
73665
3.1%
83921
3.3%
94096
3.4%
103575
3.0%
ValueCountFrequency (%)
312208
1.8%
303853
3.2%
293580
3.0%
283946
3.3%
273802
3.2%
264147
3.5%
254160
3.5%
243993
3.3%
233616
3.0%
223596
3.0%

num_weekend_nights
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9275986264
Minimum0
Maximum19
Zeros51998
Zeros (%)43.6%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile2
Maximum19
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9986134946
Coefficient of variation (CV)1.076557755
Kurtosis7.174066064
Mean0.9275986264
Median Absolute Deviation (MAD)1
Skewness1.38004645
Sum110746
Variance0.9972289116
MonotonicityNot monotonic
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
051998
43.6%
233308
27.9%
130626
25.7%
41855
 
1.6%
31259
 
1.1%
6153
 
0.1%
579
 
0.1%
860
 
0.1%
719
 
< 0.1%
911
 
< 0.1%
Other values (7)22
 
< 0.1%
ValueCountFrequency (%)
051998
43.6%
130626
25.7%
233308
27.9%
31259
 
1.1%
41855
 
1.6%
579
 
0.1%
6153
 
0.1%
719
 
< 0.1%
860
 
0.1%
911
 
< 0.1%
ValueCountFrequency (%)
191
 
< 0.1%
181
 
< 0.1%
163
 
< 0.1%
142
 
< 0.1%
133
 
< 0.1%
125
 
< 0.1%
107
 
< 0.1%
911
 
< 0.1%
860
0.1%
719
 
< 0.1%

num_workweek_nights
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct35
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.500301533
Minimum0
Maximum50
Zeros7645
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum50
Range50
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.908285615
Coefficient of variation (CV)0.7632221914
Kurtosis24.28455482
Mean2.500301533
Median Absolute Deviation (MAD)1
Skewness2.862249242
Sum298511
Variance3.641553989
MonotonicityNot monotonic
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
233684
28.2%
130310
25.4%
322258
18.6%
511077
 
9.3%
49563
 
8.0%
07645
 
6.4%
61499
 
1.3%
101036
 
0.9%
71029
 
0.9%
8656
 
0.5%
Other values (25)633
 
0.5%
ValueCountFrequency (%)
07645
 
6.4%
130310
25.4%
233684
28.2%
322258
18.6%
49563
 
8.0%
511077
 
9.3%
61499
 
1.3%
71029
 
0.9%
8656
 
0.5%
9231
 
0.2%
ValueCountFrequency (%)
501
 
< 0.1%
421
 
< 0.1%
411
 
< 0.1%
402
 
< 0.1%
351
 
< 0.1%
341
 
< 0.1%
331
 
< 0.1%
321
 
< 0.1%
305
< 0.1%
261
 
< 0.1%

num_adults
Real number (ℝ≥0)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.856403384
Minimum0
Maximum55
Zeros403
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q32
95-th percentile3
Maximum55
Range55
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5792609988
Coefficient of variation (CV)0.3120340137
Kurtosis1352.115116
Mean1.856403384
Median Absolute Deviation (MAD)0
Skewness18.31780476
Sum221636
Variance0.3355433048
MonotonicityNot monotonic
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
289680
75.1%
123027
 
19.3%
36202
 
5.2%
0403
 
0.3%
462
 
0.1%
265
 
< 0.1%
272
 
< 0.1%
202
 
< 0.1%
52
 
< 0.1%
551
 
< 0.1%
Other values (4)4
 
< 0.1%
ValueCountFrequency (%)
0403
 
0.3%
123027
 
19.3%
289680
75.1%
36202
 
5.2%
462
 
0.1%
52
 
< 0.1%
61
 
< 0.1%
101
 
< 0.1%
202
 
< 0.1%
265
 
< 0.1%
ValueCountFrequency (%)
551
 
< 0.1%
501
 
< 0.1%
401
 
< 0.1%
272
 
< 0.1%
265
 
< 0.1%
202
 
< 0.1%
101
 
< 0.1%
61
 
< 0.1%
52
 
< 0.1%
462
0.1%

num_children
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size932.9 KiB
0.0
110796 
1.0
 
4861
2.0
 
3652
3.0
 
76
10.0
 
1

Length

Max length4
Median length3
Mean length3.000008376
Min length3

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0110796
92.8%
1.04861
 
4.1%
2.03652
 
3.1%
3.076
 
0.1%
10.01
 
< 0.1%
(Missing)4
 
< 0.1%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
0.0110796
92.8%
1.04861
 
4.1%
2.03652
 
3.1%
3.076
 
0.1%
10.01
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

num_babies
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
0
118473 
1
 
900
2
 
15
9
 
1
10
 
1

Length

Max length2
Median length1
Mean length1.000008376
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0118473
99.2%
1900
 
0.8%
215
 
< 0.1%
91
 
< 0.1%
101
 
< 0.1%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
0118473
99.2%
1900
 
0.8%
215
 
< 0.1%
101
 
< 0.1%
91
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

breakfast
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size116.7 KiB
True
92310 
False
27080 
ValueCountFrequency (%)
True92310
77.3%
False27080
 
22.7%

country
Categorical

HIGH CARDINALITY

Distinct177
Distinct (%)0.1%
Missing488
Missing (%)0.4%
Memory size932.9 KiB
PRT
48590 
GBR
12129 
FRA
10415 
ESP
8568 
DEU
7287 
Other values (172)
31913 

Length

Max length3
Median length3
Mean length2.989243242
Min length2

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)< 0.1%

Sample

1st rowPRT
2nd rowPRT
3rd rowGBR
4th rowGBR
5th rowGBR

Common Values

ValueCountFrequency (%)
PRT48590
40.7%
GBR12129
 
10.2%
FRA10415
 
8.7%
ESP8568
 
7.2%
DEU7287
 
6.1%
ITA3766
 
3.2%
IRL3375
 
2.8%
BEL2342
 
2.0%
BRA2224
 
1.9%
NLD2104
 
1.8%
Other values (167)18102
 
15.2%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
prt48590
40.9%
gbr12129
 
10.2%
fra10415
 
8.8%
esp8568
 
7.2%
deu7287
 
6.1%
ita3766
 
3.2%
irl3375
 
2.8%
bel2342
 
2.0%
bra2224
 
1.9%
nld2104
 
1.8%
Other values (167)18102
 
15.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

market_segment
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.467576849
Minimum0
Maximum7
Zeros12606
Zeros (%)10.6%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q33
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.420967068
Coefficient of variation (CV)0.5758552439
Kurtosis-0.09120561313
Mean2.467576849
Median Absolute Deviation (MAD)1
Skewness0.403801563
Sum294604
Variance2.019147409
MonotonicityNot monotonic
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
256477
47.3%
324219
20.3%
519811
 
16.6%
012606
 
10.6%
15295
 
4.4%
4743
 
0.6%
7237
 
0.2%
62
 
< 0.1%
ValueCountFrequency (%)
012606
 
10.6%
15295
 
4.4%
256477
47.3%
324219
20.3%
4743
 
0.6%
519811
 
16.6%
62
 
< 0.1%
7237
 
0.2%
ValueCountFrequency (%)
7237
 
0.2%
62
 
< 0.1%
519811
 
16.6%
4743
 
0.6%
324219
20.3%
256477
47.3%
15295
 
4.4%
012606
 
10.6%

distribution_channel
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
2
97870 
0
14645 
1
 
6677
4
 
193
3
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row2

Common Values

ValueCountFrequency (%)
297870
82.0%
014645
 
12.3%
16677
 
5.6%
4193
 
0.2%
35
 
< 0.1%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
297870
82.0%
014645
 
12.3%
16677
 
5.6%
4193
 
0.2%
35
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

repeated_guest
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
0
115580 
1
 
3810

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0115580
96.8%
13810
 
3.2%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
0115580
96.8%
13810
 
3.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

num_previous_cancellations
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08711784907
Minimum0
Maximum26
Zeros112906
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum26
Range26
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8443363842
Coefficient of variation (CV)9.691887405
Kurtosis674.0736926
Mean0.08711784907
Median Absolute Deviation (MAD)0
Skewness24.45804872
Sum10401
Variance0.7129039296
MonotonicityNot monotonic
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0112906
94.6%
16051
 
5.1%
2116
 
0.1%
365
 
0.1%
2448
 
< 0.1%
1135
 
< 0.1%
431
 
< 0.1%
2626
 
< 0.1%
2525
 
< 0.1%
622
 
< 0.1%
Other values (5)65
 
0.1%
ValueCountFrequency (%)
0112906
94.6%
16051
 
5.1%
2116
 
0.1%
365
 
0.1%
431
 
< 0.1%
519
 
< 0.1%
622
 
< 0.1%
1135
 
< 0.1%
1312
 
< 0.1%
1414
 
< 0.1%
ValueCountFrequency (%)
2626
< 0.1%
2525
< 0.1%
2448
< 0.1%
211
 
< 0.1%
1919
 
< 0.1%
1414
 
< 0.1%
1312
 
< 0.1%
1135
< 0.1%
622
< 0.1%
519
 
< 0.1%

num_previous_stays
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1370969093
Minimum0
Maximum72
Zeros115770
Zeros (%)97.0%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum72
Range72
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.497436848
Coefficient of variation (CV)10.92246977
Kurtosis767.2452097
Mean0.1370969093
Median Absolute Deviation (MAD)0
Skewness23.53979995
Sum16368
Variance2.242317113
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0115770
97.0%
11542
 
1.3%
2580
 
0.5%
3333
 
0.3%
4229
 
0.2%
5181
 
0.2%
6115
 
0.1%
788
 
0.1%
870
 
0.1%
960
 
0.1%
Other values (63)422
 
0.4%
ValueCountFrequency (%)
0115770
97.0%
11542
 
1.3%
2580
 
0.5%
3333
 
0.3%
4229
 
0.2%
5181
 
0.2%
6115
 
0.1%
788
 
0.1%
870
 
0.1%
960
 
0.1%
ValueCountFrequency (%)
721
< 0.1%
711
< 0.1%
701
< 0.1%
691
< 0.1%
681
< 0.1%
671
< 0.1%
661
< 0.1%
651
< 0.1%
641
< 0.1%
631
< 0.1%

reserved_room
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
A
85994 
D
19201 
E
 
6535
F
 
2897
G
 
2094
Other values (5)
 
2669

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowC
2nd rowC
3rd rowA
4th rowA
5th rowA

Common Values

ValueCountFrequency (%)
A85994
72.0%
D19201
 
16.1%
E6535
 
5.5%
F2897
 
2.4%
G2094
 
1.8%
B1118
 
0.9%
C932
 
0.8%
H601
 
0.5%
P12
 
< 0.1%
L6
 
< 0.1%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
a85994
72.0%
d19201
 
16.1%
e6535
 
5.5%
f2897
 
2.4%
g2094
 
1.8%
b1118
 
0.9%
c932
 
0.8%
h601
 
0.5%
p12
 
< 0.1%
l6
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

changes_between_booking_arrival
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct21
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2211240472
Minimum0
Maximum21
Zeros101314
Zeros (%)84.9%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum21
Range21
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6523055727
Coefficient of variation (CV)2.949953118
Kurtosis79.39360467
Mean0.2211240472
Median Absolute Deviation (MAD)0
Skewness6.000270054
Sum26400
Variance0.4255025601
MonotonicityNot monotonic
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0101314
84.9%
112701
 
10.6%
23805
 
3.2%
3927
 
0.8%
4376
 
0.3%
5118
 
0.1%
663
 
0.1%
731
 
< 0.1%
817
 
< 0.1%
98
 
< 0.1%
Other values (11)30
 
< 0.1%
ValueCountFrequency (%)
0101314
84.9%
112701
 
10.6%
23805
 
3.2%
3927
 
0.8%
4376
 
0.3%
5118
 
0.1%
663
 
0.1%
731
 
< 0.1%
817
 
< 0.1%
98
 
< 0.1%
ValueCountFrequency (%)
211
 
< 0.1%
201
 
< 0.1%
181
 
< 0.1%
172
 
< 0.1%
162
 
< 0.1%
153
< 0.1%
145
< 0.1%
135
< 0.1%
122
 
< 0.1%
112
 
< 0.1%

deposit_policy
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
No Deposit
104641 
Non Refund
14587 
Refundable
 
162

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo Deposit
2nd rowNo Deposit
3rd rowNo Deposit
4th rowNo Deposit
5th rowNo Deposit

Common Values

ValueCountFrequency (%)
No Deposit104641
87.6%
Non Refund14587
 
12.2%
Refundable162
 
0.1%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
deposit104641
43.9%
no104641
43.9%
refund14587
 
6.1%
non14587
 
6.1%
refundable162
 
0.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

id_travel_agency_booking
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct333
Distinct (%)0.3%
Missing16340
Missing (%)13.7%
Infinite0
Infinite (%)0.0%
Mean86.69338185
Minimum1
Maximum535
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum1
5-th percentile1
Q19
median14
Q3229
95-th percentile250
Maximum535
Range534
Interquartile range (IQR)220

Descriptive statistics

Standard deviation110.7745476
Coefficient of variation (CV)1.277773981
Kurtosis-0.007179564938
Mean86.69338185
Median Absolute Deviation (MAD)13
Skewness1.089385636
Sum8933753
Variance12271.00041
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
931961
26.8%
24013922
11.7%
17191
 
6.0%
143640
 
3.0%
73539
 
3.0%
63290
 
2.8%
2502870
 
2.4%
2411721
 
1.4%
281666
 
1.4%
81514
 
1.3%
Other values (323)31736
26.6%
(Missing)16340
13.7%
ValueCountFrequency (%)
17191
 
6.0%
2162
 
0.1%
31336
 
1.1%
447
 
< 0.1%
5330
 
0.3%
63290
 
2.8%
73539
 
3.0%
81514
 
1.3%
931961
26.8%
10260
 
0.2%
ValueCountFrequency (%)
5353
 
< 0.1%
53168
0.1%
52735
< 0.1%
52610
 
< 0.1%
5102
 
< 0.1%
50910
 
< 0.1%
5086
 
< 0.1%
50224
 
< 0.1%
4971
 
< 0.1%
49557
< 0.1%

id_person_booking
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct352
Distinct (%)5.2%
Missing112593
Missing (%)94.3%
Infinite0
Infinite (%)0.0%
Mean189.2667353
Minimum6
Maximum543
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum6
5-th percentile40
Q162
median179
Q3270
95-th percentile435
Maximum543
Range537
Interquartile range (IQR)208

Descriptive statistics

Standard deviation131.6550146
Coefficient of variation (CV)0.6956056721
Kurtosis-0.4907952103
Mean189.2667353
Median Absolute Deviation (MAD)111
Skewness0.6015996673
Sum1286446
Variance17333.04288
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40927
 
0.8%
223784
 
0.7%
67267
 
0.2%
45250
 
0.2%
153215
 
0.2%
174149
 
0.1%
219141
 
0.1%
281138
 
0.1%
154133
 
0.1%
405119
 
0.1%
Other values (342)3674
 
3.1%
(Missing)112593
94.3%
ValueCountFrequency (%)
61
 
< 0.1%
81
 
< 0.1%
937
< 0.1%
101
 
< 0.1%
111
 
< 0.1%
1214
 
< 0.1%
149
 
< 0.1%
165
 
< 0.1%
181
 
< 0.1%
2050
< 0.1%
ValueCountFrequency (%)
5432
 
< 0.1%
5411
 
< 0.1%
5392
 
< 0.1%
5342
 
< 0.1%
5311
 
< 0.1%
5305
 
< 0.1%
5282
 
< 0.1%
52515
< 0.1%
52319
< 0.1%
5217
 
< 0.1%

customer_type
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
0
89613 
2
25124 
1
 
4076
3
 
577

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
089613
75.1%
225124
 
21.0%
14076
 
3.4%
3577
 
0.5%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
089613
75.1%
225124
 
21.0%
14076
 
3.4%
3577
 
0.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

avg_price
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct8726
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.7187443
Minimum0
Maximum300
Zeros1960
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile38.4
Q169.29
median94.575
Q3126
95-th percentile193.5
Maximum300
Range300
Interquartile range (IQR)56.71

Descriptive statistics

Standard deviation47.8237708
Coefficient of variation (CV)0.4701569129
Kurtosis1.597201678
Mean101.7187443
Median Absolute Deviation (MAD)27.825
Skewness0.9413424229
Sum12144200.88
Variance2287.113054
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
623754
 
3.1%
752715
 
2.3%
902473
 
2.1%
652418
 
2.0%
01960
 
1.6%
801889
 
1.6%
951661
 
1.4%
1201607
 
1.3%
1001573
 
1.3%
851538
 
1.3%
Other values (8716)97802
81.9%
ValueCountFrequency (%)
01960
1.6%
0.261
 
< 0.1%
0.51
 
< 0.1%
115
 
< 0.1%
1.291
 
< 0.1%
1.481
 
< 0.1%
1.562
 
< 0.1%
1.61
 
< 0.1%
1.81
 
< 0.1%
212
 
< 0.1%
ValueCountFrequency (%)
300290
0.2%
299.431
 
< 0.1%
299.332
 
< 0.1%
299.21
 
< 0.1%
29910
 
< 0.1%
298.711
 
< 0.1%
2985
 
< 0.1%
297.571
 
< 0.1%
297.51
 
< 0.1%
297.381
 
< 0.1%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size932.9 KiB
0
111974 
1
 
7383
2
 
28
3
 
3
8
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0111974
93.8%
17383
 
6.2%
228
 
< 0.1%
33
 
< 0.1%
82
 
< 0.1%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
0111974
93.8%
17383
 
6.2%
228
 
< 0.1%
33
 
< 0.1%
82
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

total_of_special_requests
Real number (ℝ≥0)

ZEROS

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5713627607
Minimum0
Maximum5
Zeros70318
Zeros (%)58.9%
Negative0
Negative (%)0.0%
Memory size932.9 KiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7927984228
Coefficient of variation (CV)1.387557043
Kurtosis1.492564811
Mean0.5713627607
Median Absolute Deviation (MAD)0
Skewness1.349189377
Sum68215
Variance0.6285293392
MonotonicityNot monotonic
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
070318
58.9%
133226
27.8%
212969
 
10.9%
32497
 
2.1%
4340
 
0.3%
540
 
< 0.1%
ValueCountFrequency (%)
070318
58.9%
133226
27.8%
212969
 
10.9%
32497
 
2.1%
4340
 
0.3%
540
 
< 0.1%
ValueCountFrequency (%)
540
 
< 0.1%
4340
 
0.3%
32497
 
2.1%
212969
 
10.9%
133226
27.8%
070318
58.9%

Interactions

Correlations

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

typecancellationdays_between_booking_arrivalyear_arrival_datemonth_arrival_dateweek_number_arrival_dateday_of_month_arrival_datenum_weekend_nightsnum_workweek_nightsnum_adultsnum_childrennum_babiesbreakfastcountrymarket_segmentdistribution_channelrepeated_guestnum_previous_cancellationsnum_previous_staysreserved_roomchanges_between_booking_arrivaldeposit_policyid_travel_agency_bookingid_person_bookingcustomer_typeavg_pricerequired_car_parking_spacestotal_of_special_requests
0Fancy Hotel03422015July2710020.00TruePRT00000C3No DepositNaNNaN00.000
1Fancy Hotel07372015July2710020.00TruePRT00000C4No DepositNaNNaN00.000
2Fancy Hotel072015July2710110.00TrueGBR00000A0No DepositNaNNaN075.000
3Fancy Hotel0132015July2710110.00TrueGBR11000A0No Deposit304.0NaN075.000
4Fancy Hotel0142015July2710220.00TrueGBR22000A0No Deposit240.0NaN098.001
5Fancy Hotel0142015July2710220.00TrueGBR22000A0No Deposit240.0NaN098.001
6Fancy Hotel002015July2710220.00TruePRT00000C0No DepositNaNNaN0107.000
7Fancy Hotel092015July2710220.00FalsePRT00000C0No Deposit303.0NaN0103.001
8Fancy Hotel1852015July2710320.00TruePRT22000A0No Deposit240.0NaN082.001
9Fancy Hotel1752015July2710320.00FalsePRT32000D0No Deposit15.0NaN0105.500

Last rows

typecancellationdays_between_booking_arrivalyear_arrival_datemonth_arrival_dateweek_number_arrival_dateday_of_month_arrival_datenum_weekend_nightsnum_workweek_nightsnum_adultsnum_childrennum_babiesbreakfastcountrymarket_segmentdistribution_channelrepeated_guestnum_previous_cancellationsnum_previous_staysreserved_roomchanges_between_booking_arrivaldeposit_policyid_travel_agency_bookingid_person_bookingcustomer_typeavg_pricerequired_car_parking_spacestotal_of_special_requests
119380Hotel0442017August35311320.00FalseDEU22000A0No Deposit9.0NaN0140.7501
119381Hotel01882017August35312320.00TrueDEU00000A0No Deposit14.0NaN099.0000
119382Hotel01352017August35302430.00TrueJPN22000G0No Deposit7.0NaN0209.0000
119383Hotel01642017August35312420.00TrueDEU32000A0No Deposit42.0NaN087.6000
119384Hotel0212017August35302520.00TrueBEL32000A0No Deposit394.0NaN096.1402
119385Hotel0232017August35302520.00TrueBEL32000A0No Deposit394.0NaN096.1400
119386Hotel01022017August35312530.00TrueFRA22000E0No Deposit9.0NaN0225.4302
119387Hotel0342017August35312520.00TrueDEU22000D0No Deposit9.0NaN0157.7104
119388Hotel01092017August35312520.00TrueGBR22000A0No Deposit89.0NaN0104.4000
119389Hotel02052017August35292720.00FalseDEU22000A0No Deposit9.0NaN0151.2002

Duplicate rows

Most frequently occurring

typecancellationdays_between_booking_arrivalyear_arrival_datemonth_arrival_dateweek_number_arrival_dateday_of_month_arrival_datenum_weekend_nightsnum_workweek_nightsnum_adultsnum_childrennum_babiesbreakfastcountrymarket_segmentdistribution_channelrepeated_guestnum_previous_cancellationsnum_previous_staysreserved_roomchanges_between_booking_arrivaldeposit_policyid_travel_agency_bookingid_person_bookingcustomer_typeavg_pricerequired_car_parking_spacestotal_of_special_requests# duplicates
20Hotel02562016October43162320.00TrueDEU22000A0No Deposit9.0333.02100.75007
2Fancy Hotel0242015November45331010.00TrueFRA11000A2No Deposit334.0281.0240.00006
14Fancy Hotel0362015November4572610.00TrueDEU11000A1No Deposit185.0281.0236.00004
13Fancy Hotel0362015November4572610.00TrueAUT11000A1No Deposit185.0281.0236.00003
0Fancy Hotel052017January121310.00TruePRT22000A0No Deposit314.029.0240.40112
1Fancy Hotel0172015November4682520.00TrueFRA11000A1No Deposit334.0281.0248.00002
3Fancy Hotel0242015November45331020.00TrueITA11000A1No Deposit326.0281.0048.00002
4Fancy Hotel0242015October442671510.00TrueAUT11000E2No Deposit185.0281.0252.20002
5Fancy Hotel0272015November4562710.00TrueFRA11000A1No Deposit334.0281.0240.00002
6Fancy Hotel0312015November45231010.00TrueAUT11000A2No Deposit185.0281.0236.00002